Computer Engineering

Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/128

Computer Engineering

Browse

Start date: 2020

Search Results

Now showing 1 - 10 of 14
  • No Thumbnail Available
    Item
    Investigating the Thresholding Effect and Fingerprint Transformation Using Cross-Correlation Similarity Matching
    (Faculty of Science Lafiya, 2025-01-17) Garuba O.R., Abdullahi, I.M., Dogo, E.M., & Maliki, D
    One of the leading diseases globally is cancer and breast cancer is not exempted. The objective of the WHO Global Breast Cancer Initiative (GBCI) is to reduce global breast cancer mortality by 2.5% per year, thereby averting 2.5 million breast cancer deaths globally between 2020 and 2040. The three pillars toward achieving these objectives are: health promotion for early detection; timely diagnosis; and comprehensive breast cancer management. In this study we propose an early and comprehensive detection technique in combating breast cancer diagnosis by combining the strength of both PSO (Particle Swarm Optimization) and BPSO (Binary Particle Swarm Optimization) to achieve optimal solution. The results obtained indicated the superiority of the Hybrid PSO-BPSO model in detection over an existing solution by achieving an accuracy of 98.82% on both the WBCD and WDBC datasets.
  • No Thumbnail Available
    Item
    Blockchain Technology in Healthcare Systems: Applications, Methodology, Problems, and Current Trends.
    (2021-04-19) Dauda, I. A., Nuhu, B. K., Abubakar, J., Abdullahi, I. M., & Maliki, D.
    Blockchain Technology (BT) is a secured ledger that has the potential to enhance the safety, quality as well as efficiency of healthcare provision. This will benefit healthcare administrators and healthcare end-users. This paper is focused on expanding the significance of blockchain technology in healthcare information. It identifies those aspects that are not being recorded by many researchers in establishing the prospects of Blockchain Technology in the healthcare domain. Accordingly, the paper looked at Blockchain involvement in administering healthcare services such as telemedicine, health information exchange, and electronic prescribing. The review can discover the huge potential of Blockchain technology in healthcare such as in storing healthcare data on a shared Block that is accessible to concerned stakeholders without undue privacy distresses. This research provides the desired guide and identified open perspectives for researchers that will improve the level of adoption of Blockchain in the healthcare domain.
  • No Thumbnail Available
    Item
    Unimodal Medical Image Registration using Elite Opposition Bacterial Foraging Optimization Algorithm
    (JOURNAL OF SCIENCE TECHNOLOGY AND EDUCATION, 2022-09-08) Maliki, D., Muazu, M.B., Kolo J.G., & Olaniyi, O.M
    Medical imaging applications frequently use image registration for a variety of purposes, and the search of an ideal image transformation parameters that align the two images (reference and floating) is still an optimization challenge. Medical image registration has been optimized using different metaheuristics optimization strategies. One method, the Bacterial Foraging Algorithm (BFOA), has issues of poor exploration and low convergence to a better solution. This research work presents the Elite Opposition Bacterial Foraging Optimization Algorithm (EOBFOA) for optimizing unimodal medical image registration. The EOBFOA is an enhanced version of Bacterial Foraging Algorithm (BFOA) using the Elite Opposition Strategy. The proposed EOBFOA uses Root Mean Square Error (RMSE) as a measure to determine the accuracy of the image registration process. The performance of the image registration using the EOBFOA was compared against other existing nature inspired algorithms. The obtained results shown that the proposed EOBFOA outperformed other algorithms in searching for the best optimum transformation parameters for the image registration.
  • No Thumbnail Available
    Item
    Development of an IoT Based Irrigation Control System using Convolutional Neural Network
    (JOURNAL OF SCIENCE TECHNOLOGY AND EDUCATION, 2023-06-22) Adamu, M., Abdul-Malik, U. T., Maliki, D
    The automation of irrigation activities has the potential to revolutionize traditional manual and static irrigation practices, leading to increased productivity with reduced human intervention. Manual irrigation practices often result in water wastage or inadequate water supply to specific crops, as different crops have varying water requirements (crop water need). Moreover, manual irrigation methods consume significant time and effort, especially when the farmland is located at a distance. This paper presents an IoT-based irrigation system that utilizes computer vision technology to capture and recognize crops in the irrigation field using a Convolutional Neural Network (CNN) model. The developed system continuously monitors and maintains the optimal soil moisture content for each specific crop, employing soil moisture and temperature sensors. The control unit of the system is implemented using the Raspberry Pi 3b+ platform. The performance of the developed system was evaluated using two key metrics: Accuracy and Response time. The CNN model achieved high accuracy, with a stabilized accuracy of 95 percent after 50 epochs of training and validation, using a dataset of 800 pictures. This indicates the system's capability to accurately identify crops in the field. The response time of the system was assessed through ten trials, resulting in an average response time of 14.3 seconds, which is considered satisfactory. The findings of this study demonstrate the effectiveness of the proposed IoT-based irrigation system in automating irrigation processes and optimizing water usage. By integrating crop recognition, soil moisture monitoring, and temperature sensing, the system ensures efficient irrigation practices, reducing water wastage and minimizing human effort. The successful implementation of the developed system paves the way for intelligent and dynamic irrigation systems, fostering higher agricultural productivity and sustainable water resource management
  • No Thumbnail Available
    Item
    An Electronic Voting System with Directed Acyclic Graph (DAG)- Based Blockchain Using ShimmerEVM
    (El-Amin University Journal of Computing (EAUJC)., 2024-04-07) Maliki. D., C. Oruche, I. M. Abdullahi, B. G Najashi, O. R. Isah
    This research introduces an innovative electronic voting system that enhances transparency, anonymity, and reliability, aiming to revolutionize both traditional and existing electronic voting methodologies. The system increases accessibility, security, and efficiency in the electoral process. Advanced web development technologies, including NextJs, TailwindCSS, TypeScript, and JWT tokens, are integrated for an improved e-voting experience. This system employs encryption and cryptographic hashes to secure sensitive information, alongside smart contracts on ShimmerEVM— a Directed Acyclic Graph (DAG)-based blockchain—to ensure data persistence and immutability. A user-friendly front-end interface serves as a portal to the web application, enabling seamless interaction with the ShimmerEVM network. A critical feature of the system is the activation of a biometric hardware component, essential for voter registration and participation. ShimmerEVM facilitates the execution of smart contracts, offering a decentralized, transparent, and secure environment without relying on traditional blockchain technology. The focus of this system is on the implementation of security-centric smart contracts, which are pivotal in maintaining voting data integrity and mitigating the risks of vote count manipulation.
  • No Thumbnail Available
    Item
    Intelligent Bi-modal Timetable-aware Biometric Attendance System for Enhanced Classroom Attendance
    (Journal of Contents Computing, 2022-08-22) Abdullah I. M., Maliki, D., Abubakar, A., Jung, Y. A., Kim, K., & Aliyu, A
    Attendance management is integral to many organizations and academic institutions. The manner in which attendance is managed has evolved over the years encompassing various techniques and methodologies. Although significant improvements have been made, existing systems are mostly standalone systems without proper monitoring and control from a central point. This makes it difficult for several attendance devices to be linked by a common scheme like a timetable schedule. This is integral because the lives of students in every academic institution revolves around a schedule of events and classes. There is also a need to maximize the use of the data generated from attendance systems to make meaningful decisions and predictions about students’ academic activities. The research led to the implementation of several modules which includes the key timetable schedule module and an elaborate API structure deployed to a central server for a centralized communication network between attendance devices instead of standalone devices as traditional systems have employed. The research also investigates factors affecting the performance of students and which of these factors is the greater determinant. From the results and dataset investigated, it was found that attendance is in fact not the primary determinant of students’ academic performance. Extra educational support, extra-curricular activities and family support are the top ranked factors affecting academic performance in accordance with the results obtained from this work.
  • No Thumbnail Available
    Item
    An Internet of Things (IoT)-based Veterinary Support System for Livestock Skin Disease Health Care using MobileNetV2
    (Journal of Contents Computing, 2022-12-04) Maliki, D., Aliyu, I., Kim, J., Ogunbase, E. F., Suleiman, A., & Abdullahi, I. M
    In this work, we present a novel approach for the early detection and diagnosis of skin diseases in farm animals, a major concern that can lead to reduced productivity, decreased animal welfare, and economic losses. Using Internet of Things (IoT) and MobileNetV2, we have developed a system that is built using Raspberry Pi for the gateway and low-power ESP 32 microcontrollers for sensor attachment. This system consists of sensors placed on the animals' bodies, including an electrocardiogram (ECG) sensor and a DS18B20 temperature sensor, which continuously monitor the animals' vital signs and skin temperature. The collected data is transmitted to a central server where it is processed using MobileNetV2, a deep learning model trained to recognize three common skin diseases in farm animals: Dermatophilosis, Dermatophycosis, and Papillomatosis. The results of this processing are then made available to animal owners and farmers through a mobile app. Our results show that the proposed system can accurately detect and diagnose skin diseases in farm animals with a high degree of recall (0.96), precision (0.96), and f1 score (0.96). The use of IoT and machine learning allows for real- time monitoring and early detection of skin diseases, which can significantly re- duce the spread of infection and improve the overall health and welfare of farm animals. In addition, the system is intended to support veterinarians in assessing the health status of farm animals. Overall, this work demonstrates the potential of using IoT and machine learning for the early detection and diagnosis of skin dis- eases in farm animals and highlights the importance of continuous monitoring and proactive management in maintaining the health and welfare of these animals
  • No Thumbnail Available
    Item
    IoT Based Security Management Framework for Heterogeneous Network Environment
    (2020) Ajibo, C. A.; Chinaeke-Ogbuka, I. M.; Dogo, E. M.; Ogbuka C. U.
    In an effort to curb the potential losses associated with the event of security bridge, admitting the uneven bandwidth support that characterizes most developing smart cities, we propose a neural inspired Multimodal Security Management System (MSMS) that is bandwidth-tolerant. The proposed system leverages on a Next-Generation Network (NGN) architecture in catering for the challenges associated with the provisioning of ubiquitous broadband access for IoT support in a heterogeneous morphological network environment. In order to evaluate the MSMS, we simulated the proposed cloud-based system on a Next Generation Network (NGN) architecture which utilizes Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) as transport technique in a Long Term Evolution (LTE) backbone infrastructure. We then compare its performance over a competitive alternative transport technique: "Internet Protocol Asynchronous Transfer Mode (IP/ATM)". Thus, we further evaluated the MEMS on the latter architecture. While, our proposed system is able to capture both textual, aural, and visual information of individuals in security vulnerable environments via installed smart microphones and cameras, it is also able to integrate this information's in predicting security threats. When compared with the popular Security Management System (SMS) "ShotSpotter", results show that our proposed system outperforms the ShotSpotter system by 0.87 and 0.45 in terms of efficiency and response time respectively. Finally, simulation of our proposed system on an IP/MPLS transport schemes shows that the former outperforms the latter with respect to overall network bandwidth utilization and average traffic loss in the ratio of 0.098 and 0.087 respectively.
  • No Thumbnail Available
    Item
    Development of a solar-powered greenhouse integrated with SMS and web notification systems
    (IGI Global, 2021) Jafta, L.; Nwulu, N.; Dogo, E.
    Energy for heating and cooling is among the biggest costs in greenhouse crop production. This has led to a rethink on energy-saving strategies, including the demand for solar energy as a viable renewable and sustainable choice for greenhouse farming. This chapter presents the development of a solar-powered system leveraging on internet of things and GSM technologies for sensing, controlling, and maintaining optimal climatic parameters inside a greenhouse. The proposed system is designed to automatically measure and monitor changes in temperature, humidity, soil moisture, and the light intensity. The strategy utilized in the design framework provides the user with the information of the measured parameters online and via SMS regardless of their geographical location. The chapter also incorporates a mechanism to self-regulate the climatic condition inside the greenhouse, suitable for the plant growth. Such a system can help improve the quantity and quality of crops grown in a greenhouse. Tests carried out on the system prove its effectiveness according to the design considerations.
  • No Thumbnail Available
    Item
    Automated Hydroponic System Integrated With an Android Smartphone Application
    (IGI Global, 2021) Nwulu, N.; Suka, D.; Dogo, E
    Hydroponics farming is fast gaining acceptance globally as an alternative and viable method of farming, instigated by the contemporary challenges posed by climate change, exploding population growth, and global food insecurity. Hydroponics farming can be greatly improved by leveraging on innovative technological advances that will allow for the effective and efficient utiliza-tion of limited natural resources such as water, energy (sunlight), and dwindling agricultural farmlands, consequently resulting in higher yields. This paper presents the design and implementation of an automated flood and drain hydroponic system with internet of things and Android application functionalities. The design is an integrated and automatic plant-watering, water level, and pH measurement and control system using Android application with wi-fi communication technology. Tests carried out proved the workability of the system in line with expected design considerations.